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Patent-based semantic measurement of one-way and two-way technology convergence: The case of ultraviolet light emitting diodes (UV-LEDs)

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  • Eilers, Kathi
  • Frischkorn, Jonas
  • Eppinger, Elisabeth
  • Walter, Lothar
  • Moehrle, Martin G.

Abstract

Companies need to identify technology convergence in order to get early warning signals to detect new risks and opportunities. The purpose of this paper is to provide a novel method for identifying different movement patterns of technology convergence by means of a semantic analysis approach using patent data. We illustrate this method on the basis of four distinct application technologies of ultraviolet light emitting diodes (UV-LEDs). Developing semantic anchor points for these four application technologies and calculating semantic similarity values for all pairs of patents and anchor points enables the identification of and separation between one-way and two-way technology convergence by means of statistical analysis.

Suggested Citation

  • Eilers, Kathi & Frischkorn, Jonas & Eppinger, Elisabeth & Walter, Lothar & Moehrle, Martin G., 2019. "Patent-based semantic measurement of one-way and two-way technology convergence: The case of ultraviolet light emitting diodes (UV-LEDs)," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 341-353.
    • Handle: RePEc:eee:tefoso:v:140:y:2019:i:c:p:341-353
    DOI: 10.1016/j.techfore.2018.12.024
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    References listed on IDEAS

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    Citations

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    Cited by:

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    3. Juite Wang & Tzu-Yen Hsu, 2023. "Early discovery of emerging multi-technology convergence for analyzing technology opportunities from patent data: the case of smart health," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4167-4196, August.
    4. de Paulo, Alex Fabianne & Nunes, Breno & Porto, Geciane, 2020. "Emerging green technologies for vehicle propulsion systems," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    5. Motohashi, Kazuyuki & Zhu, Chen, 2023. "Identifying technology opportunity using dual-attention model and technology-market concordance matrix," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    6. Sick, Nathalie & Bröring, Stefanie, 2022. "Exploring the research landscape of convergence from a TIM perspective: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. MOTOHASHI Kazuyuki, 2023. "Identifying Technology Opportunity Using a Dual-attention Model and a Technology-market Concordance Matrix," Discussion papers 23024, Research Institute of Economy, Trade and Industry (RIETI).
    8. Zhu, Chen & Motohashi, Kazuyuki, 2022. "Identifying the technology convergence using patent text information: A graph convolutional networks (GCN)-based approach," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    9. Nicola Melluso & Andrea Bonaccorsi & Filippo Chiarello & Gualtiero Fantoni, 2021. "Rapid detection of fast innovation under the pressure of COVID-19," Papers 2102.00197, arXiv.org.
    10. Moehrle, Martin G. & Frischkorn, Jonas, 2021. "Bridge strongly or focus – An analysis of bridging patents in four application fields of carbon fiber reinforcements," Journal of Informetrics, Elsevier, vol. 15(2).

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